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Relevant bibliographies by topics / DDI interaction

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Academic literature on the topic 'DDI interaction'

Author: Grafiati

Published: 5 June 2025

Last updated: 1 August 2025

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Journal articles on the topic "DDI interaction"

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Bahar, Muh Akbar, Pauline Lanting, Jens H. J. Bos, Rolf H. Sijmons, Eelko Hak, and Bob Wilffert. "Impact of Drug-Gene-Interaction, Drug-Drug-Interaction, and Drug-Drug-Gene-Interaction on (es)Citalopram Therapy: The PharmLines Initiative." Journal of Personalized Medicine 10, no. 4 (2020): 256. http://dx.doi.org/10.3390/jpm10040256.

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We explored the association between CYP2C19/3A4 mediated drug-gene-interaction (DGI), drug-drug-interaction (DDI) and drug-drug-gene-interaction (DDGI) and (es)citalopram dispensing course. A cohort study was conducted among adult Caucasians from the Lifelines cohort (167,729 participants) and linked dispensing data from the IADB.nl database as part of the PharmLines Initiative. Exposure groups were categorized into (es)citalopram starters with DGI, DDI and DDGI. The primary outcome was drug switching and/or dose adjustment, and the secondary was early discontinuation after the start of (es)ci

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Kibrom, Samson, Zelalem Tilahun, and Solomon Assefa Huluka. "Potential Drug-Drug Interactionsamong Adult Patients Admitted to MedicalWards at a Tertiary Teaching Hospital inEthiopia." Journal of Drug Delivery and Therapeutics 8, no. 5-s (2018): 348–54. http://dx.doi.org/10.22270/jddt.v8i5-s.2056.

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 Abstract Introduction: A Drug-drug interaction (DDI) is a decrease or increase in the pharmacological or clinical response to the administration of two or more drugs that are different from the anticipated response they initiate when individually administered. Objectives: To assess the prevalence and factors associated with potential DDIs among adult inpatients admitted to the medical wards of a tertiary teaching Hospital in Ethiopia. Methods: A retrospective cross-sectional study design was employed on adult patients who were admitted to the medical ward in one year p

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Yap, Kevin Yi-Lwern, Alexandre Chan, and Keung Chui Wai. "Opinions on Drug Interaction Sources in Anticancer Treatments and Parameters for an Oncology-Specific Database by Pharmacy Practitioners in Asia." Health Services Insights 3 (January 2010): HSI.S3679. http://dx.doi.org/10.4137/hsi.s3679.

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Cancer patients undergoing chemotherapy are particularly susceptible to drug-drug interactions (DDIs). Practitioners should keep themselves updated with the most current DDI information, particularly involving new anticancer drugs (ACDs). Databases can be useful to obtain up-to-date DDI information in a timely and efficient manner. Our objective was to investigate the DDI information sources of pharmacy practitioners in Asia and their views on the usefulness of an oncology-specific database for ACD interactions. A qualitative, cross-sectional survey was done to collect information on the respo

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Hu, Fang-Qi, and Ju-Kui Xue. "Breathing dynamics of a trapped impurity in a dipolar Bose gas." Modern Physics Letters B 28, no. 22 (2014): 1450185. http://dx.doi.org/10.1142/s0217984914501851.

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With the consideration of impurity-bosons coupling and dipole–dipole interactions (DDI), we study the breathing dynamics of a harmonically trapped impurity interacting with a separately trapped background of dipolar Bose gas. By using the variational approach, the breathing equations, the breathing frequencies and the effective potentials governing the breathing dynamics of the impurity in dipolar gas are obtained. The effects of DDI, impurity-bosons interaction and external trapping potentials on breathing dynamics of impurity are discussed. We find that, because of the anisotropic and long-r

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Rajeev Kumar Bhaskar. "High-Order Multimodal Interaction Network for Efficient Prediction of Drug-Drug Interaction." Communications on Applied Nonlinear Analysis 32, no. 2s (2024): 113–20. http://dx.doi.org/10.52783/cana.v32.2256.

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The pharmaceutical industry places a lot of focus on preventing drug-drug interactions (DDIs). Medication interaction detection has been the primary emphasis of machine learning-based DDI prediction methods. Since studies have shown that DDIs can cause different future occurrences, it is more beneficial to predict DDI connected events while examining the mechanism behind combination medicine consumption or adverse reactions. The areas of medication development and illness diagnostics are seeing increased usage of a developing approach that predicts DDIs-associated occurrences. We examine poten

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Moura, Cristiano Soares, Francisco Assis Acurcio, and Najara Oliveira Belo. "Drug-Drug Interactions Associated with Length of Stay and Cost of Hospitalization." Journal of Pharmacy & Pharmaceutical Sciences 12, no. 3 (2009): 266. http://dx.doi.org/10.18433/j35c7z.

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Purpose To evaluate the prevalence of drug-drug interactions (DDI) in prescriptions of hospitalized patients and to identify risk factors associated. Methods A retrospective cross-sectional analysis of prescription data and medical records from a public hospital in Brazil was conducted to identify potential DDI. An inappropriate drug combination was identified and classified with a standard drug interaction source. The main diagnoses were classified with Charlson Comorbidity Index (CCI). Sex, age, polypharmacy and length of stay, among other variables, were correlated with the frequency of pot

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Swathi Mirthika, G. L., and B. Sivakumar. "A Systematic Review on Drug Interaction Prediction Using Various Methods to Reduce Adverse Effects." International Journal of Information Systems and Social Change 14, no. 1 (2023): 1–8. http://dx.doi.org/10.4018/ijissc.329233.

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Interaction prediction between the drugs is a preeminent task. Drug - drug interaction (DDI) causes serious effects to human life. The adverse effect can result in death when the interaction is not known. Predicting all DDI is a challenging mission as it requires much time. Health care professionals and care givers may not be aware of all potential drug interactions. Many studies have been carried out to predict the DDI in meticulous way. Drug banks play the major role in providing information about the drugs; through drug banks we could predict the adverse effect while using two or more drugs

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Sudsakorn, Sirimas, Praveen Bahadduri, Jennifer Fretland, and Chuang Lu. "2020 FDA Drug-drug Interaction Guidance: A Comparison Analysis and Action Plan by Pharmaceutical Industrial Scientists." Current Drug Metabolism 21, no. 6 (2020): 403–26. http://dx.doi.org/10.2174/1389200221666200620210522.

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Background: In January 2020, the US FDA published two final guidelines, one entitled “In vitro Drug Interaction Studies - Cytochrome P450 Enzyme- and Transporter-Mediated Drug Interactions Guidance for Industry” and the other entitled “Clinical Drug Interaction Studies - Cytochrome P450 Enzyme- and Transporter-Mediated Drug Interactions Guidance for Industry”. These were updated from the 2017 draft in vitro and clinical DDI guidance. Methods: This study is aimed to provide an analysis of the updates along with a comparison of the DDI guidelines published by the European Medicines Agency (EMA)

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Liu, Shengyu, Buzhou Tang, Qingcai Chen, and Xiaolong Wang. "Drug-Drug Interaction Extraction via Convolutional Neural Networks." Computational and Mathematical Methods in Medicine 2016 (2016): 1–8. http://dx.doi.org/10.1155/2016/6918381.

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Drug-drug interaction (DDI) extraction as a typical relation extraction task in natural language processing (NLP) has always attracted great attention. Most state-of-the-art DDI extraction systems are based on support vector machines (SVM) with a large number of manually defined features. Recently, convolutional neural networks (CNN), a robust machine learning method which almost does not need manually defined features, has exhibited great potential for many NLP tasks. It is worth employing CNN for DDI extraction, which has never been investigated. We proposed a CNN-based method for DDI extrac

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Sari, Flori R., Saiful Anwar, Risahmawati, Marita Fadhilah, and Fika Ekayanti. "A Clinical-Based Drug Interaction Alert (CIDIA) System for Preventing Drug Interaction and Its Associated Factors at Rural Primary Care Centres." Bangladesh Journal of Medical Science 22, no. 3 (2023): 667–75. http://dx.doi.org/10.3329/bjms.v22i3.66962.

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Objectives: Drug-drug interaction (DDI) occurs following the prescription of more than one drug. DDI and its associated factors in Indonesia’s country’s primary care have not been reported. Materials and Methods: Through this descriptive cross-sectional study, we analysed the DDI incidence using the Clinical-Based Drug Interaction Alert (CIDIA) alert system. Purposive research was carried out by analysing prescriptions (n=2410) from nine primary health cares. Results: CIDIA alert system detected 7.5% DDI incidence in all prescriptions, categorized as mild (63%), moderate (36%) and

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Dissertations / Theses on the topic "DDI interaction"

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Zhang, Jing. "Design and implementation of DNA-Directed Immobilisation (DDI) glycoarrays for probing carbohydrate-protein interactions." Phd thesis, Ecole Centrale de Lyon, 2010. http://tel.archives-ouvertes.fr/tel-00605541.

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Dupin, Lucie. "Validation et criblage de nouvelles molécules anti-infectieuses sur microarray : applications à Pseudomonas aeruginosa." Thesis, Lyon, 2016. http://www.theses.fr/2016LYSEC018/document.

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Pseudomonas aeruginosa (PA) est la troisième bactérie impliquée dans les maladies nosocomiales et est la principale cause de mortalité des patients atteints de la mucoviscidose. PA est résistante à la plupart des traitements antibiotiques. Trouver de nouvelles stratégies thérapeutiques est devenu un enjeu majeur de santé publique, l’une d’entre elles est l’inhibition de facteurs de virulence. Parmi ceux-ci, les lectines sont des protéines impliquées dans l’adhésion et la formation de biofilm via des interactions avec des sucres (PA-IL, PA- IIL, FliC, FliD, PilA, PilY1 et CupB6).Le but de ce tr

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Goudot, Alice. "Développement d'une plateforme de criblage pour la recherche de nouvelles molécules anti-infectieuses : applications à Pseudomonas aeruginosa." Thesis, Ecully, Ecole centrale de Lyon, 2013. http://www.theses.fr/2013ECDL0023/document.

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Pseudomonas aeruginosa (PA) est l’un des principaux germes impliqués dans les maladies nosocomiales et est aussi la principale cause de mortalité et morbidité des patients atteints de la mucoviscidose malgré l’utilisation massive d’antibiotiques. Dans la lutte contre PA, une alternative aux antibiotiques est l’inhibition de ses facteurs de virulence notamment ceux impliqués dans l’adhésion et la formation du biofilm via des interactions de type sucres/protéines. Ces protéines sont appelées lectines (PA-IL, PA-IIL, FliD). L’objectif de ce travail est la recherche de molécules inhibitrices (glyc

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Li, Mengyao. "USING SEMIPHYSIOLOGICALLY-BASED PHARMACOKINETIC (SEMI-PBPK) MODELING TO EXPLORE THE IMPACT OF DIFFERENCES BETWEEN THE INTRAVENOUS (IV) AND ORAL (PO) ROUTE OF ADMINISTRATION ON THE MAGNITUDE AND TIME COURSE OF CYP3A-MEDIATED METABOLIC DRUG-DRUG INTERACTIONS (DDI) USING MIDAZOLAM (MDZ) AS PROTOTYPICAL SUBSTRATE AND FLUCONAZOLE (FLZ) AND ERYTHROMYCIN (ERY) AS PROTOTYPICAL INHIBITORS." VCU Scholars Compass, 2016. http://scholarscompass.vcu.edu/etd/4402.

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The purpose of the project was to investigate the impact of IV and PO routes difference for MDZ, a prototypical CYP3A substrate, and two CYP3A inhibitors (CYP3AI) -FLZ and ERY-, on the magnitude and time course of their inhibitory metabolic DDI. Individual semi-PBPK models for MDZ, FLZ and ERY were developed and validated separately, using pharmacokinetic (PK) parameters from clinical/in-vitro studies and published physiological parameters. Subsequently, DDI sub-models between MDZ and CYP3AIs incorporated non-competitive and mechanism-based inhibition (MBI) for FLZ and ERY, respectively, on he

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Lemma, Dechassa Mekonnen. "SWI/SNF-nucleosome interactions and disassembly of nucleosomes : novel methodologies for mapping protein-protein and protein-DNA interaction /." Available to subscribers only, 2009. http://proquest.umi.com/pqdweb?did=1791777401&sid=9&Fmt=2&clientId=1509&RQT=309&VName=PQD.

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Thesis (Ph. D.)--Southern Illinois University Carbondale, 2009.<br>"Molecular Biology, Microbiology and Biochemistry." Keywords: Nucleosomes, Protein-DNA interaction, Protein-protein interactions. Includes bibliographical references (p. 123-152). Also available online.

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Pugin, Laurent. "Interaction with Music Encoding." Allitera Verlag, 2016. https://slub.qucosa.de/id/qucosa%3A23351.

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Desai, Shital H. "Embodied intuitive interaction in children." Thesis, Queensland University of Technology, 2017. https://eprints.qut.edu.au/112766/8/112766.pdf.

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Children are increasingly using complex products which makes it essential that these products should be intuitive to use. This research studied the role of Embodiment in intuitive interaction in children. Children were observed playing with Jenga (both the physical version and the app), Monkey Blocks – a gravity defying stacking toy and Osmo – a mixed reality toy. The research resulted in an interaction model that will help designers to design Embodied intuitive products for children. The outcomes build on the ongoing research in intuitive interaction and provide insight into how designers cou

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Dadi, Anis [Verfasser], and Carsten [Akademischer Betreuer] Müller. "Nuclear Processes in Intense Light-Matter Interaction / Anis Dadi ; Betreuer: Carsten Müller." Heidelberg : Universitätsbibliothek Heidelberg, 2012. http://d-nb.info/1179784669/34.

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Steed, Anthony James. "Defining interaction within immersive virtual environments." Thesis, Online version, 1996. http://ethos.bl.uk/OrderDetails.do?did=1&uin=uk.bl.ethos.243940.

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Herold, Christoph, Eugene P. Petrov, and Petra Schwille. "DNA interaction with freestanding cationic lipid bilayers." Diffusion fundamentals 11 (2009) 112, S. 1, 2009. https://ul.qucosa.de/id/qucosa%3A14086.

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Books on the topic "DDI interaction"

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Riva, Giuseppe. Psicologia dei nuovi media. 2nd ed. Il mulino, 2008.

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Cristofori, Cecilia. Stato di moratoria: Le rappresentazioni sociali dei giovani dall'autonomia alla segregazione sociale. F. Angeli, 1990.

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Rabbone, Maria Teresa. INBA/RAF project: Interactive Network of Byzantine Art. FFG srl, 2001.

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Society), National Dialogue on Decentralization (1996 Nepal Law. National Dialogue on Decentralization: A report of the proceedings of the interaction of DWC with DDC presidents and government officials : proceedings report. Nepal Law Society, 1996.

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1947-, Graedon Teresa, ed. Yong yao bao dian: Xian dai ren de chi yao xin zhu zhang = The people's guide to deadly drug interactions. Yue dan chu ban she gu fen you xian gong si, 1998.

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Clulow, Adam, and Tristan Mostert, eds. The Dutch and English East India Companies. Amsterdam University Press, 2019. http://dx.doi.org/10.5117/9789462985278.

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The Dutch and English East India Companies were formidable organisations that were gifted with expansive powers that allowed them to conduct diplomacy, raise armies and seize territorial possessions. But they did not move into an empty arena in which they were free to deploy these powers without resistance. Early modern Asia stood at the center of the global economy and was home to powerful states and sprawling commercial networks. The companies may have been global enterprises but they operated in a globalised region in which they encountered a range of formidable competitors who frequently o

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Geological Survey (U.S.), ed. HAZPAC, An Interactive Map of Pacific Rim Natural Hazards, Population, and Infrastructure, U.S. Geological Survey, Digital Data Series DDS-76, 2002, (CD-ROM). s.n., 2002.

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Hongxin, Dan. Xin shi dai jiao hu ying yu: New era interactive English : Shi ting shuo xue sheng yong shu Viewing, listening & speaking companion book. 2nd ed. Qing hua da xue chu ban she, 2008.

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You, Junsheng. Jin dai Tianjin yu zhou bian qu xian de jing ji hu dong yan jiu: Study on economic interactions between Tianjin and its surrounding counties in modern times. Beijing li gong da xue chu ban she, 2016.

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Capretti, Paolo, Cecilia Comparini, Matteo Garbelotto, and Nicola La Porta, eds. XIII Conference "Root and Butt Rot of Forest Trees" IUFRO Working Party 7.02.01. Firenze University Press, 2013. http://dx.doi.org/10.36253/978-88-6655-353-3.

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The present Proceedings comprise the contributions that were presented at the 13th International Conference of the IUFRO W. Party 7.02.01 “Root and Butt Rot of Forest Trees” that was held in Italy from the 4th to the 10th of September 2011. The Conference started in Firenze than moved to FEM Research Centre, S. Michele all’Adige, Trento and continued in San Martino di Castrozza, Dolomite region. Root and Butt Rot of Forest Trees have a high biological and economic impact in forestry. The Proceedings were organized under seven headings: Genomics and Plant-Pathogen Interactions; Systematics, Tax

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Book chapters on the topic "DDI interaction"

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Zhao, Hengpeng, Shuoyu Cui, Xiaoli Lin, and Ping Liang. "BIOFUSE-DDI: A Dual-Source Transformer Framework for Drug-Drug Interaction Prediction." In Lecture Notes in Computer Science. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-95-0030-7_15.

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Bleasby, Kelly, Xiaoyan Chu, and Raymond Evers. "In Vitro Techniques to Study Transporter-Based DDI." In Enzyme- and Transporter-Based Drug-Drug Interactions. Springer New York, 2009. http://dx.doi.org/10.1007/978-1-4419-0840-7_9.

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Stoner, Chad L., Michael R. Wester, and Benjamin J. Burke. "In Silico Approaches to Predict DDIs." In Enzyme- and Transporter-Based Drug-Drug Interactions. Springer New York, 2009. http://dx.doi.org/10.1007/978-1-4419-0840-7_6.

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Hwang, Seok-min, Hee-Jun Park, and Jong-ha Lee. "A Study on a Mask R-CNN-Based Diagnostic System Measuring DDH Angles on Ultrasound Scans." In Intelligent Human Computer Interaction. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-68452-5_29.

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Jain, Abhishek, and Zhengzhong Jin. "Non-interactive Zero Knowledge from Sub-exponential DDH." In Lecture Notes in Computer Science. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-77870-5_1.

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Testa, Enrico. "Leopardi e il letamaio. Note stilistiche su Fiori italiani." In Biblioteca di Studi di Filologia Moderna. Firenze University Press, 2024. https://doi.org/10.36253/979-12-215-0565-8.20.

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The article focuses on a fundamental principle of Meneghello’s writing: the interactions. For this purpose, it analyses some passages from Fiori italiani and explores their thematic and stylistic structure.

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Vijayan, Alpha, and B. S. Chandrasekar. "An Ensemble BERT CHEM DDI for Prediction of Side Effects in Drug–Drug Interactions." In International Conference on Innovative Computing and Communications. Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-3679-1_47.

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Rossetti, Edoardo. "Giudizi universali. Reti devozionali e tensioni escatologiche attorno ai gesuati milanesi." In Le vestigia dei gesuati. Firenze University Press, 2020. http://dx.doi.org/10.36253/978-88-5518-228-7.15.

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This essay provides an outline of the familial, social, and cultural network of the Milanese Jesuati between the end of the fifteenth century and the first decades of the sixteenth century. Particular attention is given to their interactions with Cardinal Bernardino López de Carvajal, one of the protagonists of the schismatic Council of Pisa-Milan (1510-1512). Starting from the creation of their settlement of San Girolamo, new documentary evidence is employed to show how the surrounding urban area and the physical buildings that should have been erected there actually mirrored the local networ

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Cooley, Richard B., and Holger Sondermann. "Probing Protein–Protein Interactions with Genetically Encoded Photoactivatable Cross-Linkers." In c-di-GMP Signaling. Springer New York, 2017. http://dx.doi.org/10.1007/978-1-4939-7240-1_26.

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Bonasia, Mattia. "Per uno studio delle transizioni narrative in Il dispatrio." In Biblioteca di Studi di Filologia Moderna. Firenze University Press, 2024. https://doi.org/10.36253/979-12-215-0565-8.12.

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The article presents a narratological study of Il dispatrio, structured by two key critical axes: the connection between autobiography and point of view. Il dispatrio is presented as a distinctly autobiographical novel, written in first person, with a rhapsodic and discontinuous development. We demonstrate how Meneghello’s transcultural identity produces a dialectic of perspectives which identifies the self in different ways through space and time. Finally, the methods by which the narrator links various situations are examined, as the narrative transitions between fragments. We aim to demonst

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Conference papers on the topic "DDI interaction"

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Song, Zhenyu, and Yang Gao. "IS-DDI: Invariant Substructure Based Method for Drug-Drug Interaction Prediction." In 2024 10th International Conference on Big Data and Information Analytics (BigDIA). IEEE, 2024. https://doi.org/10.1109/bigdia63733.2024.10808895.

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Mondal, Ishani. "BERTChem-DDI : Improved Drug-Drug Interaction Prediction from text using Chemical Structure Information." In Proceedings of Knowledgeable NLP: the First Workshop on Integrating Structured Knowledge and Neural Networks for NLP. Association for Computational Linguistics, 2020. http://dx.doi.org/10.18653/v1/2020.knlp-1.4.

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Chen, Ke, Xiaosong Han, Xiaoran Li, Yanchun Liang, Dong Xu, and Renchu Guan. "PNESR-DDI: An Effective Drug-Drug Interaction Prediction Model Based on Pretraining Method and Enhanced Subgraph Reconstruction." In 2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE, 2024. https://doi.org/10.1109/bibm62325.2024.10822475.

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Cai, Xiangwen, Haijun Lei, Zhenquan Wu, Hai Xie, Guoming Zhang, and Baiying Lei. "DCI-FQA: Dual-Branch Cross Interaction Network for Fundus Quality Assessment." In 2024 IEEE International Symposium on Biomedical Imaging (ISBI). IEEE, 2024. http://dx.doi.org/10.1109/isbi56570.2024.10635483.

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Hassan, Basim A., and Marwa Muthana Mohammed. "A New Class of Dai-Liao Method for Solving Iteration Problems." In 2025 7th International Congress on Human-Computer Interaction, Optimization and Robotic Applications (ICHORA). IEEE, 2025. https://doi.org/10.1109/ichora65333.2025.11017075.

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Segall, S. M., R. A. Gummow, and R. G. Reid. "New Concepts in the Prioritization of Multiple ECDA Indications." In CORROSION 2007. NACE International, 2007. https://doi.org/10.5006/c2007-07161.

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Abstract This paper describes the challenge of integrating specific types of ECDA indications, such as AC-enhanced corrosion (ACEC) and DC interference (DCI), under the prioritization criteria recommended by NACE RP0502-2002. Starting from the observation that the risk of corrosion does not always increase with the size of the holiday, the paper analyzes the interaction of up to four complementary ECDA indications (i.e. CIPS, DCVG, ACEC and DCI), with and without prior history of corrosion, as a function of their severity. New concepts, such as “distributed indication ” and “relevant indicatio

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Chu, Xu, Yang Lin, Yasha Wang, Leye Wang, Jiangtao Wang, and Jingyue Gao. "MLRDA: A Multi-Task Semi-Supervised Learning Framework for Drug-Drug Interaction Prediction." In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/628.

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Drug-drug interactions (DDIs) are a major cause of preventable hospitalizations and deaths. Recently, researchers in the AI community try to improve DDI prediction in two directions, incorporating multiple drug features to better model the pharmacodynamics and adopting multi-task learning to exploit associations among DDI types. However, these two directions are challenging to reconcile due to the sparse nature of the DDI labels which inflates the risk of overfitting of multi-task learning models when incorporating multiple drug features. In this paper, we propose a multi-task semi-supervised

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Lyu, Tengfei, Jianliang Gao, Ling Tian, Zhao Li, Peng Zhang, and Ji Zhang. "MDNN: A Multimodal Deep Neural Network for Predicting Drug-Drug Interaction Events." In Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}. International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/ijcai.2021/487.

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The interaction of multiple drugs could lead to serious events, which causes injuries and huge medical costs. Accurate prediction of drug-drug interaction (DDI) events can help clinicians make effective decisions and establish appropriate therapy programs. Recently, many AI-based techniques have been proposed for predicting DDI associated events. However, most existing methods pay less attention to the potential correlations between DDI events and other multimodal data such as targets and enzymes. To address this problem, we propose a Multimodal Deep Neural Network (MDNN) for DDI events predic

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Lin, Xuan, Zhe Quan, Zhi-Jie Wang, Tengfei Ma, and Xiangxiang Zeng. "KGNN: Knowledge Graph Neural Network for Drug-Drug Interaction Prediction." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/380.

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Drug-drug interaction (DDI) prediction is a challenging problem in pharmacology and clinical application, and effectively identifying potential DDIs during clinical trials is critical for patients and society. Most of existing computational models with AI techniques often concentrate on integrating multiple data sources and combining popular embedding methods together. Yet, researchers pay less attention to the potential correlations between drug and other entities such as targets and genes. Moreover, recent studies also adopted knowledge graph (KG) for DDI prediction. Yet, this line of method

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Wang, Ziyan, Zhankun Xiong, Feng Huang, Xuan Liu, and Wen Zhang. "ZeroDDI: A Zero-Shot Drug-Drug Interaction Event Prediction Method with Semantic Enhanced Learning and Dual-modal Uniform Alignment." In Thirty-Third International Joint Conference on Artificial Intelligence {IJCAI-24}. International Joint Conferences on Artificial Intelligence Organization, 2024. http://dx.doi.org/10.24963/ijcai.2024/671.

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Drug-drug interactions (DDIs) can result in various pharmacological changes, which can be categorized into different classes known as DDI events (DDIEs). In recent years, previously unobserved/unseen DDIEs have been emerging, posing a new classification task when unseen classes have no labelled instances in the training stage, which is formulated as a zero-shot DDIE prediction (ZS-DDIE) task. However, existing computational methods are not directly applicable to ZS-DDIE, which has two primary challenges: obtaining suitable DDIE representations and handling the class imbalance issue. To overcom

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Reports on the topic "DDI interaction"

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Herbers, Thomas H., and Tim T. Janssen. In-Situ Wave Observations in the High Resolution Air-Sea Interaction DRI. Defense Technical Information Center, 2009. http://dx.doi.org/10.21236/ada531916.

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Herbers, Thomas H., and Tim T. Janssen. In-Situ Wave Observations in the High Resolution Air-Sea Interaction DRI. Defense Technical Information Center, 2007. http://dx.doi.org/10.21236/ada573362.

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Herbers, Thomas H., and Tim T. Janssen. In-Situ Wave Observations in the High Resolution Air-Sea Interaction DRI. Defense Technical Information Center, 2012. http://dx.doi.org/10.21236/ada590695.

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Terrill, Eric J. X-band Observations of Waves, Algorithm Development, and Validation High Resolution Wave-Air-Sea Interaction DRI. Defense Technical Information Center, 2012. http://dx.doi.org/10.21236/ada574656.

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Friedlander, Michael, Clinton Dawes, and Y. (Joel) Kashman. The Interaction between Epiphytes and Seaweeds. United States Department of Agriculture, 1995. http://dx.doi.org/10.32747/1995.7571355.bard.

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Two Israeli laboratories (IOLR and TAU) cooperated with one American laboratory (USF) in the research of the interaction between epiphytes (Ulva sp.) and the cultivated seaweed (Gracilaria sp.) The main objectives included the following aspects: Structural aspects, effects of different irradiances on growth, sensitivity studies, allelopathic excretions, selective chemicals and integration of studies of epiphytization. The studies were operated in outdoor tanks, indoor growth chambers and in the lab. The main conclusions and their relevance for mariculture are as following: 1. The green algal e

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Ramnath, Rishabh, Neale Kinnear, Sritika Chowdhury, and T. Hyatt. Interacting with Android Auto and Apple CarPlay when driving: The effect on driver performance. TRL, 2020. http://dx.doi.org/10.58446/sjxj5756.

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This study aimed to assess the impact of interacting with two infotainment systems, Android Auto and Apple CarPlay, on four driver performance measures: reaction time, driving behaviour, eyes-off road and self-reported performance. It also compared the results with other forms of driver impairment studied previously. Twenty regular Android users took part in the Android Auto trial and 20 regular Apple users took part in the Apple CarPlay trial. Each participant completed three 20 minute drives in TRL’s DigiCar simulator: control (no interaction with infotainment system), voice enabled and touc

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Cenedese, Claudia, and Mary-Louise Timmermans. 2017 program of studies: ice-ocean interactions. Woods Hole Oceanographic Institution, 2018. http://dx.doi.org/10.1575/1912/27807.

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The 2017 Geophysical Fluid Dynamics Summer Study Program theme was Ice-Ocean Interactions. Three principal lecturers, Andrew Fowler (Oxford), Adrian Jenkins (British Antarctic Survey) and Fiamma Straneo (WHOI/Scripps Institution of Oceanography) were our expert guides for the first two weeks. Their captivating lectures covered topics ranging from the theoretical underpinnings of ice-sheet dynamics, to models and observations of ice-ocean interactions and high-latitude ocean circulation, to the role of the cryosphere in climate change. These icy topics did not end after the first two weeks. Sev

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Gurevitz, Michael, Michael E. Adams, Boaz Shaanan, et al. Interacting Domains of Anti-Insect Scorpion Toxins and their Sodium Channel Binding Sites: Structure, Cooperative Interactions with Agrochemicals, and Application. United States Department of Agriculture, 2001. http://dx.doi.org/10.32747/2001.7585190.bard.

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Integrated pest management in modern crop protection may combine chemical and biological insecticides, particularly due to the risks to the environment and livestock arising from the massive use of non-selective chemicals. Thus, there is a need for safer alternatives, which target insects more specifically. Scorpions produce anti-insect selective polypeptide toxins that are biodegradable and non-toxic to warm-blooded animals. Therefore, integration of these substances into insect pest control strategies is of major importance. Moreover, clarification of the molecular basis of this selectivity

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Bennett, Richard H., Conrad Curry, Kenneth J. Curry, and Matthew Hulbert. Seafloor Sediment Permeability and Fabric Studies In Support of the ONR-DRI Program High Frequency Sound Interaction in Ocean Sediments. Defense Technical Information Center, 2002. http://dx.doi.org/10.21236/ada627791.

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Or, Etti, Tai-Ping Sun, Amnon Lichter, and Avichai Perl. Characterization and Manipulation of the Primary Components in Gibberellin Signaling in the Grape Berry. United States Department of Agriculture, 2010. http://dx.doi.org/10.32747/2010.7592649.bard.

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Seedless cultivars dominate the table grape industry. In these cultivars it is mandatory to apply gibberellin (GA) to stimulate berry development to a commercially acceptable size. These cultivars differ in their sensitivity to GA application, and it frequently results in adverse effects such as decreased bud fertility and increased fruit drop. Our long term goals are to (1) understand the molecular basis for the differential sensitivity and identify markers for selection of sensitive cultivars (2) to develop new strategies for targeted manipulation of the grape berry response to GA that will

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